Java中 ThreadPoolExecutor 类学习笔记

1、定义

Java中的线程池。ThreadPoolExecutor类是接口Executor的实现类。如下图所示： 

2、作用

线程池解决两个不同的问题：由于每个任务的调用开销减少，它们通常在执行大量异步任务时提供改进的性能，并且它们提供了一种限制和管理资源（包括执行一个任务。 每个ThreadPoolExecutor还维护一些基本统计信息，例如已完成任务的数量。

3、创建类解释

ThreadPoolExecutor extends AbstractExecutorService。

构造方法：

public ThreadPoolExecutor(int corePoolSize,                              int maximumPoolSize,                              long keepAliveTime,                              TimeUnit unit,                              BlockingQueue
     
       workQueue,                              ThreadFactory threadFactory,                              RejectedExecutionHandler handler) {        if (corePoolSize < 0 ||            maximumPoolSize <= 0 ||            maximumPoolSize < corePoolSize ||            keepAliveTime < 0)            throw new IllegalArgumentException();        if (workQueue == null || threadFactory == null || handler == null)            throw new NullPointerException();        this.corePoolSize = corePoolSize;        this.maximumPoolSize = maximumPoolSize;        this.workQueue = workQueue;        this.keepAliveTime = unit.toNanos(keepAliveTime);        this.threadFactory = threadFactory;        this.handler = handler;    }
     

其中：

1. 　　corePoolSize ： 线程池的核心线程数，即使空闲时仍保留在池中的线程数，除非设置 allowCoreThreadTimeOut.
2. 　　maximumPoolSize : 池中允许的最大线程数
3.        keepAliveTime :  线程的存活时间。当线程池里的线程数大于corePoolSize时，如果等了keepAliveTime时长还没有任务可执行，则线程退出。
4.        unit  : 指定keepAliveTime的单位
5.        workQueue :  一个阻塞队列，提交的任务将会被放到这个队列里
6.    　threadFactory :  执行程序创建新线程时使用的工厂
7.        handler : 执行被阻止时使用的处理程序，因为达到线程限制和队列容量 

4.线程池执行流程

任务被提交到线程池，会先判断当前线程数量是否小于corePoolSize，如果小于则创建线程来执行提交的任务，否则将任务放入workQueue队列，如果workQueue满了，则判断当前线程数量是否小于maximumPoolSize,如果小于则创建线程执行任务，否则就会调用handler，以表示线程池拒绝接收任务。

 5.线程池的几个主要方法分析

5.1 主方法：ThreadPoolExector的execute

public void execute(Runnable command) {

if (command == null)            throw new NullPointerException();        /*         * Proceed in 3 steps:         *         * 1. If fewer than corePoolSize threads are running, try to         * start a new thread with the given command as its first         * task.  The call to addWorker atomically checks runState and         * workerCount, and so prevents false alarms that would add         * threads when it shouldn't, by returning false.         *         * 2. If a task can be successfully queued, then we still need         * to double-check whether we should have added a thread         * (because existing ones died since last checking) or that         * the pool shut down since entry into this method. So we         * recheck state and if necessary roll back the enqueuing if         * stopped, or start a new thread if there are none.         *         * 3. If we cannot queue task, then we try to add a new         * thread.  If it fails, we know we are shut down or saturated         * and so reject the task.         */ 　　　　　　 　　　　　//1 当前运行的线程数量小于核心线程数量，直接将任务加入worker启动运行。        int c = ctl.get();        if (workerCountOf(c) < corePoolSize) {            if (addWorker(command, true))                return;            c = ctl.get();        } 　

　　/**

　　2 运行线程数量大于核心线程数量时，上面的if分支针对大于corePoolSize，并且缓存队列加入任务操作成功的情况。

　　运行中并且将任务加入缓冲队列成功，正常来说这样已经完成了处理逻辑。

　　但是为了保险起见，增加了状态出现异常的确认判断，如果状态出现异常会继续remove操作，如果执行true，则按照拒绝处理策略驳回任务；

　　*/

        if (isRunning(c) && workQueue.offer(command)) {

int recheck = ctl.get();            if (! isRunning(recheck) && remove(command))                reject(command);            else if (workerCountOf(recheck) == 0)                addWorker(null, false);        }

　　/**

　　3 这里针对运行线程数量超过了corePoolSize，并且缓存队列也已经放满的情况。

　　注意第二个参数是false，可以在下面addWorker方法看到，就是针对线程池最大线程数量maximumPoolSize的判断。

　　*/

　　else if (!addWorker(command, false))            reject(command);　　} }

 5.2 关键方法：ThreadPoolExector的addWorker（增加工作线程）

private boolean addWorker(Runnable firstTask, boolean core) {        retry:        for (;;) {            int c = ctl.get();            int rs = runStateOf(c);            // Check if queue empty only if necessary.            if (rs >= SHUTDOWN &&                ! (rs == SHUTDOWN &&                   firstTask == null &&                   ! workQueue.isEmpty()))                return false;            for (;;) {                int wc = workerCountOf(c);                if (wc >= CAPACITY ||                    wc >= (core ? corePoolSize : maximumPoolSize)) //创建非核心线程时，即core等于false。判断当前线程数是否大于等于maximumPoolSize，如果大于等于则返回false                    return false;                if (compareAndIncrementWorkerCount(c))                    break retry;                c = ctl.get();  // Re-read ctl                if (runStateOf(c) != rs)                    continue retry;                // else CAS failed due to workerCount change; retry inner loop            }        }        boolean workerStarted = false;        boolean workerAdded = false;        Worker w = null;        try {            w = new Worker(firstTask);            final Thread t = w.thread;//创建Worker对象，同时也会实例化一个Thread，并启动。            if (t != null) {                final ReentrantLock mainLock = this.mainLock;                mainLock.lock();                try {                    // Recheck while holding lock.                    // Back out on ThreadFactory failure or if                    // shut down before lock acquired.                    int rs = runStateOf(ctl.get());                    if (rs < SHUTDOWN ||                        (rs == SHUTDOWN && firstTask == null)) {                        if (t.isAlive()) // precheck that t is startable                            throw new IllegalThreadStateException();                        workers.add(w);                        int s = workers.size();                        if (s > largestPoolSize)                            largestPoolSize = s;                        workerAdded = true;                    }                } finally {                    mainLock.unlock();                }                if (workerAdded) {                    t.start();                    workerStarted = true;                }            }        } finally {            if (! workerStarted)                addWorkerFailed(w);        }        return workerStarted;    }

5.3 Worker中的runWorker方法，也是worker中的run方法主体。

/** Delegates main run loop to outer runWorker  */ public void run() {      runWorker(this); }

/**     * Main worker run loop.  Repeatedly gets tasks from queue and     * executes them, while coping with a number of issues:     *     * 1. We may start out with an initial task, in which case we     * don't need to get the first one. Otherwise, as long as pool is     * running, we get tasks from getTask. If it returns null then the     * worker exits due to changed pool state or configuration     * parameters.  Other exits result from exception throws in     * external code, in which case completedAbruptly holds, which     * usually leads processWorkerExit to replace this thread.     *     * 2. Before running any task, the lock is acquired to prevent     * other pool interrupts while the task is executing, and then we     * ensure that unless pool is stopping, this thread does not have     * its interrupt set.     *     * 3. Each task run is preceded by a call to beforeExecute, which     * might throw an exception, in which case we cause thread to die     * (breaking loop with completedAbruptly true) without processing     * the task.     *     * 4. Assuming beforeExecute completes normally, we run the task,     * gathering any of its thrown exceptions to send to afterExecute.     * We separately handle RuntimeException, Error (both of which the     * specs guarantee that we trap) and arbitrary Throwables.     * Because we cannot rethrow Throwables within Runnable.run, we     * wrap them within Errors on the way out (to the thread's     * UncaughtExceptionHandler).  Any thrown exception also     * conservatively causes thread to die.     *     * 5. After task.run completes, we call afterExecute, which may     * also throw an exception, which will also cause thread to     * die. According to JLS Sec 14.20, this exception is the one that     * will be in effect even if task.run throws.     *     * The net effect of the exception mechanics is that afterExecute     * and the thread's UncaughtExceptionHandler have as accurate     * information as we can provide about any problems encountered by     * user code.     *     * @param w the worker     */    final void runWorker(Worker w) {        Thread wt = Thread.currentThread();        Runnable task = w.firstTask;        w.firstTask = null;        w.unlock(); // allow interrupts        boolean completedAbruptly = true;        try {            while (task != null || (task = getTask()) != null) {
    //线程调用runWoker，会while循环调用getTask方法从workerQueue里读取任务，然后执行任务                w.lock();                // If pool is stopping, ensure thread is interrupted;                // if not, ensure thread is not interrupted.  This                // requires a recheck in second case to deal with                // shutdownNow race while clearing interrupt                if ((runStateAtLeast(ctl.get(), STOP) ||                     (Thread.interrupted() &&                      runStateAtLeast(ctl.get(), STOP))) &&                    !wt.isInterrupted())                    wt.interrupt();                try {                    beforeExecute(wt, task);                    Throwable thrown = null;                    try {                        task.run();//只要getTask方法不返回null,此线程就不会退出。                    } catch (RuntimeException x) {                        thrown = x; throw x;                    } catch (Error x) {                        thrown = x; throw x;                    } catch (Throwable x) {                        thrown = x; throw new Error(x);                    } finally {                        afterExecute(task, thrown);                    }                } finally {                    task = null;                    w.completedTasks++;                    w.unlock();                }            }            completedAbruptly = false;        } finally {            processWorkerExit(w, completedAbruptly);        } }

5.4 getTask方法实现

* Performs blocking or timed wait for a task, depending on     * current configuration settings, or returns null if this worker     * must exit because of any of:     * 1. There are more than maximumPoolSize workers (due to     *    a call to setMaximumPoolSize).     * 2. The pool is stopped.     * 3. The pool is shutdown and the queue is empty.     * 4. This worker timed out waiting for a task, and timed-out     *    workers are subject to termination (that is,     *    {
     @code allowCoreThreadTimeOut || workerCount > corePoolSize})     *    both before and after the timed wait, and if the queue is     *    non-empty, this worker is not the last thread in the pool.     *     * @return task, or null if the worker must exit, in which case     *         workerCount is decremented     */    private Runnable getTask() {        boolean timedOut = false; // Did the last poll() time out?        for (;;) {            int c = ctl.get();            int rs = runStateOf(c);            // Check if queue empty only if necessary.            if (rs >= SHUTDOWN && (rs >= STOP || workQueue.isEmpty())) {                decrementWorkerCount();                return null;            }            int wc = workerCountOf(c);            // Are workers subject to culling?            boolean timed = allowCoreThreadTimeOut || wc > corePoolSize;　　　　　　　 　　　　　　　//如果运行线程数超过了最大线程数，但是缓存队列已经空了，这时递减worker数量。 　　　　　　　//如果有设置允许线程超时或者线程数量超过了核心线程数量，并且线程在规定时间内均未poll到任务且队列为空则递减worker数量 if ((wc > maximumPoolSize || (timed && timedOut))                && (wc > 1 || workQueue.isEmpty())) {                if (compareAndDecrementWorkerCount(c))                    return null;                continue;            }            try {                Runnable r = timed ?                    workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :                    workQueue.take();                if (r != null)                    return r;                timedOut = true;            } catch (InterruptedException retry) {                timedOut = false;            }        }  }